These general image forgery detection or localization methods usually rely on different forgery clues or footprints left by the forgery operation, such as JPEG artifacts [1]}, [2]}, edge inconsistency [3]}, [4]}, noise pattern [5]}, [6]}, camera model [7]}, EXIF inconsistency [8]}, etc., to detect or localize forgery. Table 1 of [9]} summarizes existing major forgery localization methods and the forgery clues the methods focus on. For example, [10]} employs LSTM based patch comparison to focus on edge inconsistency between the tampered patches and authentic patches. CAT-Net [11]} leverages DCT coefficients to focus on resampling clues.
